Feedback Cancellation Filter Tone Removal
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Solution Overview
Problem
Existing sound processing devices, such as hearing aids, face challenges in effectively canceling acoustic feedback, particularly when input signals include tonal and periodic components, leading to instability and distortion, as current feedback cancellation techniques often misidentify tonal signals as feedback, resulting in inadequate cancellation and audible artefacts.
Innovation Solution
The implementation of a sound processing method using finite impulse response (FIR) filters with tone removal blocks that apply whitening filters to both input and output signals before they enter the least mean squares (LMS) stage, ensuring that the feedback cancellation filter adapts at a normal rate and accurately models the feedback path without being entrained by tonal signals, thereby preventing filter corruption and maintaining effective feedback cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback cancellation techniques are used to reduce acoustic feedback, then feedback oscillation and instability are reduced, but tonal input signals such as music are inappropriately filtered and audible artefacts are produced
Solution Approach 1:
The system segments the signal processing by separating tonal signal detection and handling from the general feedback cancellation processing. Tone detection identifies tonal components in the input signal, and tone suppression selectively attenuates these tones before they can corrupt the feedback cancellation filter, while preserving non-tonal signals for normal feedback cancellation processing.
Solution Approach 2:
The patent introduces intermediate processing stages including tone detection and tone suppression blocks that act as mediators between the input signal and the feedback cancellation filter. These intermediaries prevent tonal signals from directly affecting the adaptive filter, thereby preventing filter corruption and audible artefacts while maintaining effective feedback cancellation.
2Reliability
If adaptive feedback cancellation is used to dynamically cancel feedback, then feedback oscillation is reduced, but filter corruption occurs when tonal signals are present
Solution Approach 1:
The system performs preliminary tone detection and suppression before the signal reaches the adaptive feedback cancellation filter. By detecting tones in advance and suppressing them beforehand, the adaptive filter is protected from attempting to adapt to tonal signals that would corrupt its response, maintaining filter stability while enabling dynamic feedback cancellation for non-tonal signals.
3Device complexity
If fixed filter response is used for feedback cancellation, then implementation is simpler, but the filter cannot adapt to changing feedback conditions
Solution Approach 1:
The patent implements dynamic adaptation of the feedback cancellation filter through adaptive filter algorithms that continuously adjust filter coefficients based on the feedback signal characteristics. The system transitions from a static fixed filter to a dynamic adaptive filter that can track and adapt to changing feedback paths, while tone suppression prevents corruption from tonal signals during this adaptation process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for robust feedback cancellation even in the presence of tonal input signals like music, preventing filter corruption and maintaining high adaptation rates, thus avoiding feedback squeal and artefacts, without requiring differentiation between tonal signals and feedback, ensuring stable and accurate sound processing.
Implementation Method 1
tone removal blocks (132, 134) which use whitening filters to remove tones from both the input signal (110) and the output signal (116) before they enter the LMS stage (124)
Implementation Method 2
a filter controller (124) which uses a least mean squares (LMS) algorithm to derive appropriate new filter taps for the filter (120), and periodically updates the filter (120) with new filter taps
Implementation Method 3
a feedback cancellation filter (120) which filters the output signal (116) to produce a feedback cancellation signal (122) that is subtracted from the input signal (110)
Data Source
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AI summary
This invention concerns a method, and a device, for feedback cancellation. This invention also concerns a computer program product comprising computer program code means to make a computer execute a procedure for feedback cancellation. The method comprises providing an adaptive feedback cancellation filter which adapts under the control of a control module, and filtering at least one input of the control module to suppress correlated signals from the input prior to the control module operating upon the input. The device comprises an adaptive feedback cancellation filter, a control module and at least one filter. The control module controls adaptation of the adaptive feedback cancellation filter. The filter suppresses correlated signals from an input to the control module prior to the control module operating upon the input.